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A knockout blow for LLMs? - by Gary Marcus - Marcus on AI

garymarcus.substack.com · 1,755 words · saved by 1 readers

Apple has a new paper; it’s pretty devastating to LLMs, a powerful followup to one from many of the same authors last year. There’s actually an interesting weakness in the new argument—which I will get to below—but the overall force of the argument is undeniably powerful. So much so that LLM advocates are already partly conceding the blow while hinting at, or at least hoping for, happier futures ahead. Wolfe lays out the essentials in a thread: § In fairness, the paper both GaryMarcus’d and Subbarao (Rao) Kambhampati’d LLMs. On the one hand, it echoes and amplifies the training distribution argument that I have been making since 1998: neural networks of various kinds can generalize within a training distribution of data they are exposed to, but their generalizations tend to break down outside that distribution. That was the crux of my 1998 paper skewering multilayer perceptrons, the ancestors of current LLM, by showing out-of-distribution failures on simple math and sentence prediction

A knockout blow for LLMs? LLM “reasoning” is so cooked they turned my name into a verb Gary Marcus Jun 07, 2025 1,442 241 241 Share Quoth Josh Wolfe, well-respected venture capitalist at Lux Capital: Ha ha ha. But What’s the fuss about? Apple has a new paper ; it’s pretty devastating to LLMs, a powerful followup to one from many of the same authors last year . There’s actually an interesting weakness in the new argument—which I will get to below—but the overall force of the argument is undeniably powerful. So much so that LLM advocates are already partly conceding the blow while hinting at, or

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